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/*=========================================================================
*
* Copyright Insight Software Consortium
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0.txt
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
*=========================================================================*/
#ifndef itkAnisotropicDiffusionImageFilter_hxx
#define itkAnisotropicDiffusionImageFilter_hxx
#include "itkAnisotropicDiffusionImageFilter.h"
namespace itk
{
/**
* Constructor
*/
template< typename TInputImage, typename TOutputImage >
AnisotropicDiffusionImageFilter< TInputImage, TOutputImage >
::AnisotropicDiffusionImageFilter()
{
this->SetNumberOfIterations(1);
m_ConductanceParameter = 1.0;
m_ConductanceScalingParameter = 1.0;
m_ConductanceScalingUpdateInterval = 1;
m_TimeStep = 0.5 / std::pow( 2.0, static_cast< double >( ImageDimension ) );
m_FixedAverageGradientMagnitude = 1.0;
m_GradientMagnitudeIsFixed = false;
}
/** Prepare for the iteration process. */
template< typename TInputImage, typename TOutputImage >
void
AnisotropicDiffusionImageFilter< TInputImage, TOutputImage >
::InitializeIteration()
{
AnisotropicDiffusionFunction< UpdateBufferType > *f =
dynamic_cast< AnisotropicDiffusionFunction< UpdateBufferType > * >
( this->GetDifferenceFunction().GetPointer() );
if ( !f )
{
throw ExceptionObject(__FILE__, __LINE__, "Anisotropic diffusion function is not set.", ITK_LOCATION);
}
f->SetConductanceParameter(m_ConductanceParameter);
f->SetTimeStep(m_TimeStep);
// Check the timestep for stability
double minSpacing;
if ( this->GetUseImageSpacing() )
{
minSpacing = this->GetInput()->GetSpacing()[0];
for ( unsigned int i = 1; i < ImageDimension; i++ )
{
if ( this->GetInput()->GetSpacing()[i] < minSpacing )
{
minSpacing = this->GetInput()->GetSpacing()[i];
}
}
}
else
{
minSpacing = 1.0;
}
if ( m_TimeStep > ( minSpacing / std::pow(2.0, static_cast< double >( ImageDimension ) + 1) ) )
{
// f->SetTimeStep(1.0 / std::pow(2.0,
// static_cast<double>(ImageDimension)));
itkWarningMacro( << "Anisotropic diffusion unstable time step: "
<< m_TimeStep << std::endl
<< "Stable time step for this image must be smaller than "
<< minSpacing / std::pow( 2.0, static_cast< double >( ImageDimension + 1 ) ) );
}
if ( m_GradientMagnitudeIsFixed == false )
{
if ( ( this->GetElapsedIterations() % m_ConductanceScalingUpdateInterval ) == 0 )
{
f->CalculateAverageGradientMagnitudeSquared( this->GetOutput() );
}
}
else
{
f->SetAverageGradientMagnitudeSquared(m_FixedAverageGradientMagnitude
*
m_FixedAverageGradientMagnitude);
}
f->InitializeIteration();
if ( this->GetNumberOfIterations() != 0 )
{
this->UpdateProgress( ( (float)( this->GetElapsedIterations() ) )
/ ( (float)( this->GetNumberOfIterations() ) ) );
}
else
{
this->UpdateProgress(0);
}
}
template< typename TInputImage, typename TOutputImage >
void
AnisotropicDiffusionImageFilter< TInputImage, TOutputImage >
::PrintSelf(std::ostream & os, Indent indent) const
{
Superclass::PrintSelf( os, indent.GetNextIndent() );
os << indent << "TimeStep: " << m_TimeStep << std::endl;
os << indent << "ConductanceParameter: "
<< m_ConductanceParameter << std::endl;
os << indent << "ConductanceScalingParameter: "
<< m_ConductanceScalingParameter << std::endl;
os << indent << "ConductanceScalingUpdateInterval: "
<< m_ConductanceScalingUpdateInterval << std::endl;
os << indent << "FixedAverageGradientMagnitude: "
<< m_FixedAverageGradientMagnitude << std::endl;
}
} // end namespace itk
#endif
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